Thomas James Cartwright, Machine Learning Engineer and Developer in Edinburgh, United Kingdom
Thomas James Cartwright

Machine Learning Engineer and Developer in Edinburgh, United Kingdom

Member since July 17, 2020
Thomas has three years of industry experience designing, developing and productionising machine learning solutions and five years of industry experience developing software solutions. He holds a Master of Science in AI (with merit) from the University of Edinburgh, specialising in traditional machine learning, deep learning, and reinforcement learning. Due to a keen interest in entrepreneurship, Thomas joined Toptal to contribute his expertise and explore new challenges.
Thomas is now available for hire


  • BlackRock
    Amazon Web Services (AWS), Artificial Intelligence (AI), Data Science, Python...
  • Getaroom
    Amazon Web Services (AWS), AWS CLI, AWS Glue, Amazon SageMaker, Amazon Athena...
  • Barrachd
    SQL, React, JavaScript, C#.NET, SciPy, NumPy, Python



Edinburgh, United Kingdom



Preferred Environment

Artificial Intelligence (AI), Machine Learning, Data Science

The most amazing...

...thing I have developed is a machine learning agent that taught a simulated robot to walk.


  • Machine Learning Engineer

    2021 - PRESENT
    • Developed and productionized machine learning models to predict financial instrument prices using Scikit-learn, PyTorch, NumPy, Pandas, Python, Docker, and AWS.
    • Managed stakeholder relationships by scoping project requirements, designing key success metrics, specifying timelines, and presenting findings.
    • Led the introduction of Agile processes for new and existing machine learning projects.
    • Presented model designs and results to technical and non-technical stakeholders.
    • Engineered a model backtesting and monitoring framework using Python, Docker, and AWS—EC2, SageMaker, and CloudWatch.
    Technologies: Amazon Web Services (AWS), Artificial Intelligence (AI), Data Science, Python, PyTorch, NumPy, Pandas, Docker, Scikit-learn
  • Machine Learning Engineer

    2019 - 2021
    • Improved and productized a deep learning NLP model—achieving a classification accuracy of over 95%.
    • Designed and implemented new models for predicting sales of new properties, therefore making property price collection more accurate and efficient.
    • Performed an analysis on large, noisy datasets before presenting the findings to nontechnical teams.
    • Increased the performance of existing machine learning models through parallelization, the user of GPUs, and refactoring of Python code.
    • Ensured AI/ML solutions are explainable to nontechnical members of staff.
    • Wrote efficient Athena queries on large, noisy datasets for data analysis and development.
    Technologies: Amazon Web Services (AWS), AWS CLI, AWS Glue, Amazon SageMaker, Amazon Athena, Amazon S3 (AWS S3), Kubernetes, Terraform, Keras, NumPy, TensorFlow, Python
  • Software Developer

    2017 - 2019
    • Developed an online app using Python (NumPy, SciPy), C# .NET, JavaScript, React, and SQL.
    • Led the design and implementation of a microservice that matched large volumes of incoming messages to complex queries. Using advanced Python and linear algebra, this service decreased processing time from minutes to less than one second.
    • Participated in the design and implementation of a component that clustered large volumes of incoming messages, therefore streamlining the data processing pipeline.
    • Worked in a team to implement data analytics software that allowed users to visualize and analyze data from millions of social media interactions every hour. This allowed clients to gain actionable insights from large volumes of unorganized data.
    • Developed integrations with a large number of social media APIs, ensuring minimal data was collected to keep operational costs low and ensure clients only saw relevant information.
    • Presented and described technically complex components to technical and nontechnical members of the team.
    Technologies: SQL, React, JavaScript, C#.NET, SciPy, NumPy, Python
  • QA Lead | Software Developer

    2014 - 2017
    • Initiated and led the entire testing process leading to fewer bugs, a more robust product, and a faster development cycle.
    • Chose the software release dates, balancing customer requirements with product quality.
    • Gathered feedback from clients to align future product developments with client needs.
    • Communicated and demonstrated the product to technical and non-technical stakeholders.
    Technologies: Selenium, Python, HTML, SQL, JavaScript, C#.NET


  • Recommendation System for Citizen Science

    A system that recommends new SciStarter projects to users on the Citizen Science web portal. The recommender system uses the user's previously completed projects, and the contents of projects, to build a profile of users interests.
    The unsupervised task clustering and user recommendation system on the SciStarter website was used to increase engagement and the quality of user task completion.


  • Languages

    Python, SQL, C#
  • Libraries/APIs

    Pandas, NumPy, TensorFlow, PyTorch, Scikit-learn, Keras
  • Other

    Recommendation Systems, Machine Learning, Artificial Intelligence (AI), Data Engineering, Deep Neural Networks, Natural Language Processing (NLP), Reinforcement Learning
  • Paradigms

    Data Science
  • Platforms

    Amazon Web Services (AWS), Docker
  • Storage

    Google Cloud


  • Master's Degree in Artificial Intelligence
    2017 - 2019
    University of Edinburgh - Edinburgh, Scotland
  • Bachelor's Degree in Mathematics
    2010 - 2014
    University of Edinburgh - Edinburgh, Scotland


  • Machine Learning Specialization
    JULY 2017 - PRESENT

To view more profiles

Join Toptal
Share it with others